HFR-DVD.  To simulate realistic blurs, one typical approach is capturing videos at a high frame rate and then averaging multiple consecutive sharp frames for blurs.
In this way, the quality of the synthetic blurry images is affected by the exposure time of devices. In particular, a lower frame rate leads to longer idling time between adjacent exposures, yielding unnatural spikes in the blur trajectories.
In this regard, previous datasets mainly tackle the issue by introducing virtual frames.
For example, Su  [1]} generate inter-frame images based on optical flow estimation.
Nah  [2]} proposed to increase the frame rate of sharp videos by interpolations with a pretrained neural network.
In contrast, we construct a High-Frame-Rate Dataset for Video Deblurring (HFR-DVD) by capturing videos at 1,000 fps with a SONY DSC-RX10 IV camera, thus avoiding the artifacts caused by automatic frame interpolation.
<FIGURE>